Medical image data, which are collected with medical imaging devices, such as X-ray devices, Magnetic Resonance Imaging (MRI) devices, Ultrasound devices, Positron Emission Tomography (PET) devices or Computed Tomography (CT) devices in the diagnostic imaging departments of medical institutions, are used for an image interpretation process called “reading” or “diagnostic reading.” After an image interpretation report is generated from the medical image data, the image interpretation report, possibly accompanied by representative images or representations of the examination, are sent to the requesting physicians. Today, these image interpretation reports are usually digitized, stored, managed and distributed in a Radiology Information System (RIS) with accompanying representative images and the original examination stored in a Picture Archiving Communication System (PACS) which is often integrated with the RIS.
Recent developments in multi-detector computed tomography (MDCT) scanners and other scanning modalities provide higher spatial and temporal resolutions than the previous-generation scanners. However, the drawback to the superior image detail and information from the MDCT scanners is the volume of datasets acquired by these scanners, especially during CT angiographic procedures. For example, in certain multi-phase acquisitions, a CT examination can generate over 6000 images with the latest scanners. Accordingly, the data sets can reach a size of several gigabytes, while the acquisition times are only measured in seconds.
Under some traditional approaches, when a physician orders an examination, the patient is scanned by the medical imaging device to collect medical image data related to certain part of the body. Afterwards, the collected medical image data is transferred to stand-alone advanced processing workstations, or to distributed software applications with similar functionality, which include a suite of post-processing tools. A technologist who has access to a workstation generates some limited static images based on the medical image data, and provides the images to the interpreting physician who may use them to support the diagnostic interpretation process, and potentially include them with the image interpretation report given to the ordering physician. Because of the limitation of this processing pipeline, often less than 5% of the data contained in the original dataset is received by the ordering physician. Also, it takes longer for the physician to perform his duty while waiting for the technologist to finish the processing. As a result, since workload and time has to be prioritized based, non-optimal diagnosis may occur, and non-optimal surgery might be performed.
A more sophisticated facility would utilize a Picture Archiving and Communication System (PACS) to store original medical image data, and distribute the data to PACS viewing stations for generating reports. Still, even with the help of PACS, workflow for processing medical image data remains under a similar approach. Once the original image data has been acquired, it is usually transferred to different medical personnel or departments for diagnostic review. Various levels of technologists process and generate intermediate images before distributing them to the ordering physicians for further review. Also, these diagnostic reviews can only be performed on a limited number of isolated PACS viewing stations or stand-alone workstations.
Even with the better technologies, when intermediate images are generated, valuable information are still either filtered out, or failed to be included, from the original image dataset. The end report may contain only a fraction of the original data, limiting the ordering physician's ability to fully take advantage of the examination that has been performed. Also, restricted access to the original image dataset hinders the ordering physician ability to perform the image processing or image review himself or herself, and hence the ordering physician is forced to rely upon the perspective of the interpreting physician, even though that perspective (one of diagnosis) may be quite different from the perspective of the ordering physician (who is then responsible for devising and implementing a therapeutic plan).
Today, it has become possible to render three-dimensional (3D) images using multiple sets of tomographic data captured from different cross-sectional positions. For 3D image processing, it is not possible to store in advance all the possible spontaneous views a physician might utilize. A complete set of original image data has to be present on a 3D processing system which can generate arbitrary 3D views in real time and on demand. Therefore, with an explosion of data volume acquired from MDCT and other scanners, transporting complete datasets across the network to various workstations puts a prohibitive burden on a facility's IT infrastructure.